Data and Analytics Engineer (AI)

Location: Remote in LATAM or the US

Company

hirify.global helps financial institutions and other clients adopt AI and turn emerging technology into measurable business outcomes.

What you will do

• Architect performant data models and single sources of truth across insurance and other business domains.
• Build and maintain data infrastructure, pipelines, automated tests, and reporting workflows using SQL, Python, dbt, and Snowflake.
• Design semantic models, views, and skill files that enable reliable natural-language queries and AI-agent reasoning.
• Define metrics, dimensions, relationships, permissions, lineage, and data definitions while maintaining data security.
• Identify data-structure and coverage gaps, track adoption after launch, and ensure production systems can be maintained by run teams.
• Create reusable playbooks and templates, document implementations, and lead technical workshops for clients and colleagues.

Requirements

• 8+ years of experience in analytics engineering, data engineering, or a related technical role, including customer-facing or cross-functional work.
• Advanced SQL skills, including complex joins, CTEs, window functions, and incremental pipeline patterns.
• Production experience with dbt projects, testing, documentation, CI/CD, data modeling, and large-scale relational datasets.
• Modern, type-hinted Python experience with data pipelines and automation workflows.
• Daily use of an AI coding assistant as a primary development tool, plus practical experience with Git, pull requests, branching, and code review.
• Experience translating business requirements into technical specifications and communicating data solutions to non-technical business leaders.

Nice to have

• Experience with Airflow or another orchestration framework.
• Familiarity with enterprise systems such as ERP, CRM, or HRIS platforms.

Culture & Benefits

• Direct collaboration with clients, engineers, and AI specialists.
• Emphasis on reusable templates, documented playbooks, and scalable implementations instead of bespoke customization.
• Opportunity to teach, facilitate, influence adoption, and help organizations introduce new ways of working.
• Equal opportunity workplace.
• H-1B visa sponsorship is not available.